Biological pattern information processing device, biological pattern information processing method and program

ABSTRACT

A biological pattern information processing device includes: a detection result obtaining unit that obtains unique region information that is detected based on biological pattern information representing a biological pattern, the unique region information representing a unique region included in the biological pattern; and a display control unit that causes the unique region to be displayed using a display attribute, based on the obtained unique region information, the display attribute being different from that for a region of the biological pattern other than the unique region.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a National Stage of International Application No.PCT/JP2016/061330 filed Mar. 31, 2016, claiming priority based onJapanese Patent Application No. 2015-074424 filed Mar. 31, 2015, thecontents of all of which are incorporated herein by reference in theirentirety.

TECHNICAL FIELD

The present invention relates to a biological pattern informationprocessing device, a biological pattern information processing methodand a program.

BACKGROUND ART

In recent years, biological authentication has been receiving attentionas one of the authentication systems for identifying individuals. Abiological pattern such as a fingerprint is a feature that does notchange with the passage of time, and so its reliability inauthentication is high. On the other hand, there is also the possibilityof unlawful acts being performed using fake biological patterns such asa fake finger, with technology also being developed to prevent suchunlawful acts.

For example, the technology disclosed in Patent Document 1 is technologyfor determining a fake finger wherein a transparent thin film has beenattached to the surface of the finger. Patent Document 1 disclosestechnology that classifies a region of an image, using colors of pixelsincluded in the captured image, into a plurality of regions including atleast a skin region and a background region, and determines whetherforeign matter is present in the vicinity of the finger, using thefeatures of the regions that have not been classified into either theskin region or the background region. According to the technology ofPatent Document 1, it is possible to detect foreign matter in thevicinity of the finger (a region having a biological pattern).

PRIOR ART DOCUMENTS Patent Documents

-   [Patent Document 1] PCT International Publication No. WO 2011/058836

DISCLOSURE OF THE INVENTION Problem to be Solved by the Invention

However, there are cases in which simply detecting foreign matter (forexample, a thin film) on the basis of color information of pixels hasbeen insufficient for preventing impropriety related to authenticationusing a biological pattern.

For example, in recent years, cases have been discovered of biologicalpatterns (for example, fingerprints) being damaged by surgicaloperations or burn injuries or the like. In such cases, when abiological pattern that has been registered in advance is damaged, it isrequired to be able to correctly perform collation or at least to detectthat there is damage. Also, it is required to present the detecteddamage to the user in a readily understandable manner.

The present invention was achieved in recognition of the aforementionedissues. An exemplary object of the present invention is to provide abiological pattern information processing device, a biological patterninformation processing method and a program that, when a biologicalpattern has a unique region due to damage or the like, can detect theunique region and present to the user the detected unique region in aneasily understandable manner.

Means for Solving the Problem

A biological pattern information processing device according to anexemplary aspect of the present invention includes: a detection resultobtaining unit that obtains unique region information that is detectedbased on biological pattern information representing a biologicalpattern, the unique region information representing a unique regionincluded in the biological pattern; and a display control unit thatcauses the unique region to be displayed using a display attribute,based on the obtained unique region information, the display attributebeing different from that for a region of the biological pattern otherthan the unique region.

In the aforementioned biological pattern information processing device,the display control unit may cause a type of the unique region to bedisplayed based on the unique region information.

In the aforementioned biological pattern information processing device,the display control unit may switch display between: display of theunique region; display of a region of the biological pattern other thanthe unique region; and both of the display of the unique region and thedisplay of the region of the biological pattern other than the uniqueregion.

In the aforementioned biological pattern information processing device,the display control unit may obtain biological pattern information thathas been repaired to biological pattern information with no uniqueregion based on the unique region information, and may cause therepaired biological pattern information to be displayed.

A biological pattern information processing method according to anexemplary aspect of the present invention includes: obtaining uniqueregion information that is detected based on biological patterninformation representing a biological pattern, the unique regioninformation representing a unique region included in the biologicalpattern; and causing the unique region to be displayed using a displayattribute, based on the obtained unique region information, the displayattribute being different from that for a region of the biologicalpattern other than the unique region.

The aforementioned biological pattern information processing method mayfurther include: causing a type of the unique region to be displayedbased on the unique region information.

The aforementioned biological pattern information processing method mayfurther include switching display between: display of the unique region;display of a region of the biological pattern other than the uniqueregion; and both of the display of the unique region and the display ofthe region of the biological pattern other than the unique region.

The aforementioned biological pattern information processing method mayfurther include: obtaining biological pattern information that has beenrepaired to biological pattern information with no unique region basedon the unique region information; and causing the repaired biologicalpattern information to be displayed.

A program according to an exemplary aspect of the present inventioncauses a computer to execute: obtaining unique region information thatis detected based on biological pattern information representing abiological pattern, the unique region information representing a uniqueregion included in the biological pattern; and causing the unique regionto be displayed using a display attribute, based on the obtained uniqueregion information, the display attribute being different from that fora region of the biological pattern other than the unique region.

Effect of the Invention

According to the present invention, when a unique region such as damageexists in a biological pattern, it is possible to present to the user ina readily understandable manner that there is that unique region. Thatis, it is possible for a user to readily distinguish where a uniqueregion is located.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram that shows the schematic functionconfiguration of the biological pattern information processing deviceaccording to the first exemplary embodiment.

FIG. 2 is a block diagram that shows the schematic functionconfiguration of the biological pattern information processing deviceaccording to the second exemplary embodiment.

FIG. 3 is a block diagram that shows the schematic functionconfiguration of the inner portion of the unique region detection unitaccording to the second exemplary embodiment.

FIG. 4A is a schematic diagram that shows an example of an abnormalpattern in a fingerprint that is the object of detection by the uniqueregion detection unit according to the second exemplary embodiment.

FIG. 4B is a schematic diagram that shows an example of a fingerprintimage that includes an abnormal ridge direction that is the object ofdetection by the unique region detection unit according to the secondexemplary embodiment.

FIG. 4C is a schematic diagram that shows an example of a fingerprintimage that includes an abnormal ridge direction that is the object ofdetection by the unique region detection unit according to the secondexemplary embodiment.

FIG. 5A is a schematic diagram that shows an example of a fingerprintimage that includes an abnormal ridge direction that is the object ofdetection by the unique region detection unit according to the secondexemplary embodiment.

FIG. 5B is a schematic diagram that shows an example of a fingerprintimage that includes an abnormal ridge direction that is the object ofdetection by the unique region detection unit according to the secondexemplary embodiment.

FIG. 5C is a schematic diagram that shows an example of a fingerprintimage that includes an abnormal ridge direction that is the object ofdetection by the unique region detection unit according to the secondexemplary embodiment.

FIG. 6A is a conceptual diagram that schematically shows a templatecorresponding to an abnormal ridge direction pattern (X type), being atemplate used by the unique region detection unit according to thesecond exemplary embodiment.

FIG. 6B is a conceptual diagram that schematically shows a templatecorresponding to an abnormal ridge direction pattern (ω type), being atemplate used by the unique region detection unit according to thesecond exemplary embodiment.

FIG. 6C is a conceptual diagram that schematically shows a templatecorresponding to an abnormal ridge direction pattern (comb type), beinga template used by the unique region detection unit according to thesecond exemplary embodiment.

FIG. 7 is a schematic diagram that conceptually shows an example of afingerprint image including ridge destruction that is the object ofdetection by the unique region detection unit according to the secondexemplary embodiment.

FIG. 8 is a schematic diagram that schematically shows ridge directionimage data prior to the directional smoothing process, being a diagramthat describes the directional smoothing process performed in the innerportion of the unique region detection unit according to the secondexemplary embodiment.

FIG. 9 is a schematic diagram that schematically shows ridge directionimage data after the directional smoothing process, being a diagram thatdescribes the directional smoothing process performed in the innerportion of the unique region detection unit according to the secondexemplary embodiment.

FIG. 10 is a schematic diagram for describing the process of cutting afingerprint that is the subject of detection by the unique regiondetection unit according to the second exemplary embodiment, being adiagram that shows the state before the cutting process.

FIG. 11 is a schematic diagram for describing the process of cutting afingerprint that is the subject of detection by the unique regiondetection unit according to the second exemplary embodiment, being adiagram that shows the state after to the cutting process.

FIG. 12 is a block diagram that shows the schematic functionconfiguration of the biological pattern information processing deviceaccording to the third exemplary embodiment.

FIG. 13 is a schematic diagram for describing a Z-plasty operation thatis the subject of detection by the unique region detection unitaccording to the third exemplary embodiment, showing an example of afingerprint image before execution of a Z-plasty operation.

FIG. 14 is a schematic diagram for describing a Z-plasty operation thatis the subject of detection by the unique region detection unitaccording to the third exemplary embodiment, showing an example of afingerprint image after execution of a Z-plasty operation.

FIG. 15 is a block diagram that shows the schematic functionconfiguration of the inner portion of a repairing unit according to thethird exemplary embodiment.

FIG. 16 is a schematic diagram that shows the method of performing arestoration process based on the image of a Z-plasty operation by therepairing unit according to the third exemplary embodiment.

FIG. 17 is a block diagram that shows the schematic functionconfiguration of the repairing unit a according to a modification of thethird exemplary embodiment.

FIG. 18 is a schematic diagram that shows an example of the userinterface of the device according to at least one of the first to thirdexemplary embodiments, relating to the process of obtaining afingerprint image.

FIG. 19 is a schematic diagram that shows an example of the userinterface of the device according to at least one of the first to thirdexemplary embodiments, relating to display control in the case of aunique region being detected in an obtained fingerprint image.

FIG. 20 is a schematic diagram that shows an example of the userinterface of the device according to at least one of the first to thirdexemplary embodiments, relating to selection of a condition of acollation process in the case of a unique region being detected in anobtained fingerprint image.

FIG. 21 is a schematic diagram that shows an example of the userinterface of the device according to at least one of the first to thirdexemplary embodiments, relating to the repair process of a damagelocation (unique region).

EMBODIMENTS FOR CARRYING OUT THE INVENTION

Next, a plurality of exemplary embodiments of the present invention willbe described referring to the appended drawings.

First Exemplary Embodiment

FIG. 1 is a block diagram that shows the schematic functionconfiguration of the biological pattern information processing deviceaccording to the first exemplary embodiment. As shown in FIG. 1, thebiological pattern information processing device 1 according to thisexemplary embodiment includes a biological pattern information obtainingunit 11, a unique region detection result obtaining unit 12, and adisplay control unit 21. The biological pattern information obtainingunit 11 is hereinbelow also referred to as an information obtaining unit11. The unique region detection result obtaining unit 12 is hereinbelowalso referred to as a detection result obtaining unit 12.

The information obtaining unit 11 obtains biological pattern informationfrom the outside. Biological pattern information is information showinga biological pattern. A biological pattern may be the pattern of afingerprint (an entire fingerprint), for example.

The detection result obtaining unit 12 obtains information (uniqueregion information) relating to a unique region of biological patterninformation detected on the basis of the biological pattern informationobtained by the information obtaining unit 11.

Specifically, the detection result obtaining unit 12 requests detectionof a unique region by passing biological pattern information passed fromthe information obtaining unit 11 to a unique region detecting unit onthe outside that is not illustrated. The detection result obtaining unit12 receives information of the unique region detection result based onthis request. The specific processing method for unique region detectionis described below. The information of the detection result received bythe unique region detection result obtaining unit includes informationindicating whether there is a unique region in the passed biologicalpattern information and information relating to the location(coordinates and the like) when a unique region does exist.

A unique region is a region in which unique biological patterninformation exists due to damage to a portion of a living body (damagedlocation) or a region in which biological pattern information isdistorted by wrinkles or the like on the surface of a living body. In aunique region, a pattern may exist that differs from the pattern thatthe living body had originally. Examples of the causes of biologicaldamage that produce a unique region include cuts and abrasions and thelike, burns, and scalding from chemicals (for example, strong acidetc.).

A specific method for detecting a unique region will be described laterin the second exemplary embodiment.

The display control unit 21 performs control so as to display thebiological display information by giving different display attributes toa region that corresponds to a unique region and a region other than theunique region, respectively, on the basis of information about theunique region obtained by the detection result obtaining unit 12. Thatis, the display control unit 21 obtains information expressing whetheror not a unique region is included in the biological pattern informationfrom the detection result obtaining unit 12. When a unique region iscontained in the biological pattern information, the display controlunit 21 obtains position information expressing the range of the uniqueregion from detection result obtaining unit 12. The display control unit21 outputs a signal such as of an image, which is the result of thecontrol, to outside. An external display unit can display an image usingthe signal such as of this image.

Examples of display attributes include color when displayed on a screenand the presence of flashing.

For example, the display control unit 21 performs control so as todisplay the unique region and the other region in different colors. Inthat example, the display control unit 21 performs control so as todisplay only the unique region in a noticeable color (for example, red),and display a region other than the unique region in an ordinary color.

In addition, for example the display control unit 21 performs control ofthe display so that only the unique region flashes while the regionother than the unique region does not flash.

Furthermore, for example, the display control unit 21 performs controlof the display so that only the colors of the unique region are inverted(that is, the luminance value is reversed for each of the primarycolors, such as RGB), while the region other than the unique region isnot inverted.

The display control unit 21 may be made to perform control of thedisplay by combining two or more of the above-mentioned displayattributes. As an example of that, the display control unit 21 uses aparticularly noticeable color for only the unique region and displaysthe unique region so that it flashes.

A specific example of display control by the display control unit 21 isdisclosed later in the description of a user interface.

A typical example of biological pattern information handled by thebiological pattern information processing device 1 is fingerprintinformation. A fingerprint is a pattern formed by ridges on the surfaceof a hand or foot. Human skin is formed by the overlapping of theepidermis and dermis. The epidermis exists in the surface side (outerside) and the dermis exists on the back side (inner side). A layercalled a papillary layer exists in the portion in contact with theepidermis and the dermis. In the vicinity of this papillary layer,irregularities exist on the dermis side, with conical portions thereofforming ridges. Sweat gland pores are arranged along the conicalportions of ridges. The pattern of the ridge formed on this dermis sideis seen as is at the epidermis side. Generally, this pattern is called afingerprint. Even if the epidermis is damaged, as long as the ridgestructure in the dermis is maintained, when the epidermis is reproduced,the pattern based on the ridge structure on the side of the originaldermis will be reproduced at the epidermis side.

Another example of biological pattern information is the pattern ofarrangement of capillary blood vessels or sweat gland pores near thesurface of a finger, rather than the fingerprint itself.

Although specific methods for obtaining fingerprints are various asfollows, a method may be implemented by suitably selecting from amongthem.

The first of the methods for obtaining a fingerprint is a method ofcapturing an image of the epidermis of a finger having a fingerprintwith a camera and obtaining the information of that image as biologicalpattern information.

The second of the methods for obtaining a fingerprint is a method ofobtaining the distribution of the electrical property at the surface ofa finger as biological pattern information, using a sensor that comesinto contact with a living body. The electrical property at the surfaceof a finger differs depending on the location due to for example theshape of the ridges and the presence of sweat gland pores, and it ispossible to obtain a two-dimensional distribution of such features aspattern information.

The third of the methods of obtaining a fingerprint is a method thattransfers a substance such as ink applied to a finger to a medium suchas paper, and reads the image obtained on that medium using an opticalscanner or the like.

The fourth of the methods of obtaining a fingerprint is a method thatobtains the pattern of the surface of a finger (living body) usingoptical coherence tomography (OCT). OCT is a method of obtaining mutualinterference that occurs due to the phase difference between light thatis directed at a measurement target and reflected from the measurementtarget and a reference light, as an optical intensity pattern image.When using OCT, by suitably changing the wavelength of light, it ispossible to obtain not only information of the surface of a finger butalso pattern information of the interior of a living body to a certaindepth from the surface (a depth of several hundred micrometers to 2000micrometers). Thereby, it is possible to utilize not only the surfacebut also the living body interior pattern as biological patterninformation. An example of pattern information in the interior of aliving body that can be utilized is the ridge pattern in the dermis, thearrangement pattern of sweat gland pores, and the arrangement pattern ofcapillary blood vessels. When obtaining pattern information of theinterior of a living body using OCT, for example, each strata at apredetermined depth is utilized as two-dimensional image information.Alternatively, by stacking multiple two-dimensional images of eachstrata, it is possible to utilize three-dimensional biological patterninformation that is thereby obtained.

When three-dimensional information is not included, the fingerprintinformation is expressed as two-dimensional information. Also, when onlythe information about a certain layer is extracted fromthree-dimensional information, the information may be expressed as atwo-dimensional image. Hereinbelow, these two-dimensional images aresometimes called “fingerprint images”.

According to the biological pattern information processing device 1described above, when biological pattern information contains a uniqueregion, it is possible to display the unique region and another regiondistinguished from each other in an easy to understand manner.

Second Exemplary Embodiment

Next, the second exemplary embodiment will be described. The descriptionthat follows will focus on matter peculiar to the second exemplaryembodiment, with the description of matter in common with the firstexemplary embodiment being omitted.

FIG. 2 is a block diagram that shows the schematic functionconfiguration of the biological pattern information processing deviceaccording to the second exemplary embodiment. As shown in FIG. 2, abiological pattern information processing device 2 according to thisexemplary embodiment includes an information obtaining unit 11, adetection result obtaining unit 12, a collating unit 116, and a displaycontrol unit 121. In this exemplary embodiment, a unique regiondetecting unit 61 and a pre-registered biological pattern informationstorage unit 62 exist as functions external to the biological patterninformation processing device 2. The functions may respectively beachieved as functions of independent devices, or may be achieved aspartial functions of another device. Also, one or both of the uniqueregion detecting unit 61 and the pre-registered biological patterninformation storage unit 62 may be realized as functions in thebiological pattern information processing device 2.

The information obtaining unit 11 has the same function as that in thefirst exemplary embodiment.

The detection result obtaining unit 12 has the same function as that infirst exemplary embodiment.

The collating unit 116 performs collation processing of the biologicalpattern information in regions other than the unique region, andbiological pattern information registered in advance in thepre-registered biological pattern information storage unit 62, among thebiological pattern information obtained by the information obtainingunit 11. The collating unit 116 obtains information relating to thepresence of a unique region and the position (range) of the uniqueregion from the detection result obtaining unit 12. The collating unit116, when performing the above-mentioned collation process, can changeat least either one of a misalignment tolerance, which is the degree towhich misalignment is allowed, and a mismatch tolerance, which is thedegree to which non-agreement is allowed. When it is understood thatthere is a unique region from the information obtained by the detectionresult obtaining unit 12, the collating unit 16 may perform adjustmentso as to change either one or both of the aforementioned tolerances sothat the tolerance becomes greater (that is, so that even if there is aslight difference, the degree of regarding there to be agreementincreases).

With regard to a fingerprint having damage due to an operation orinjury, the region excluding the operated or injured portion (that is,the unique region) maintains the original fingerprint feature quantity.By inspecting the consistency of this portion, it is possible to performcollation with the fingerprint prior to the operation or injury. Forexample, in feature point collation, the determination of whether or nota fingerprint is the same is based on whether adjacent feature points ofthe fingerprint (end point and/or branch point of a ridge) have adefinite distance difference or a definite angle difference. In the caseof an operation on a fingerprint, as a result of shape change due topulling during suturing, this tolerance often ends up being exceeded.

Therefore, with respect to a fingerprint that is determined to be adamaged fingerprint, by relaxing the misalignment tolerance and themismatch tolerance of a fingerprint feature during collation beyond thestandard values, it becomes possible to create a device characterized bybeing capable of performing collation with a person's finger prior tothe damage.

When the collation tolerance is eased, the downside is an increased riskof a different person being mistakenly identified as the personconcerned. However, regarding the final determination of whether twopeople are the same person, in an operational environment in which anoperator separately carries out a final check using facial photographsbesides fingerprints, it is possible to reduce the risk of suchmisidentification.

The collation process by the collating unit 116 can be performed usingthe prior art. The outline of the process that performs collation offingerprints is as follows. For the collation process, the collatingunit 116 extracts a feature of a fingerprint image that is input.Examples of a feature include the ridge direction of a fingerprint, astatistical value relating to the distribution of that direction, theway in which ridges are connected, the number per type of ridge singularpoints, the mutual positional relations of feature points, thedirections of straight lines that connect a plurality of feature points,and the angle defined by those straight lines. Singular points of ridgesare directional singular points called circular cores, semicircularcores and deltas. The collating unit 116 evaluates the aforementionedfeatures in a plurality of fingerprint images in terms of their nearnessand/or farness in a feature space and thereby determines whether theplurality of fingerprint images are the same or not. In one example, fora fingerprint image registered in a database in advance and afingerprint image that has been newly input, the collating unit 116compares the features and determines whether or not both images agree.

In such a collation process, the aforementioned position deviationtolerance is a value indicating for example the degree to whichpositional error of the feature point in a fingerprint image is allowed.The mismatch tolerance is a value that expresses the degree to which,when two fingerprint images to be compared do not completely match, theimages are regarded as matching regardless of the extent of featuremismatch. Mismatch tolerance may for example be expressed by a distanceappropriately defined in a feature space, and may be expressed by thedegree of the weighting of the penalty to be given according to thatdistance.

The display control unit 121 has the same function as the displaycontrol unit 21 in the first exemplary embodiment. The display controlunit 121 performs control to perform display according to the collationresult by the collating unit 116. As an example, the display controlunit 121, as a result of collation by the collating unit 116, displays aportion in which a match is seen with a special display attribute (forexample, a special color).

The unique region detecting unit 61 performs processing that analyzesthe biological pattern information passed from the outside, anddetermines whether a unique region is contained in the biologicalpattern information. The unique region detecting unit 61 outputsinformation indicating whether or not there is a unique region as adecision result. When a unique region is included in the biologicalpattern information, the unique region detecting unit 61 outputsinformation on the position (position information indicating the rangeof the region). Details of the determination process by the uniqueregion detecting unit 61 will be given later.

The pre-registered biological pattern information storage unit 62 storesbiological pattern information registered in advance. The pre-registeredbiological pattern information storage unit 62 associates and holdsbiological pattern information and identification information foridentifying individuals. The pre-registered biological patterninformation storage unit 62 may also associate and hold theabove-mentioned identification information and attribute information ofindividuals. Examples of attribute information of an individual are aname, information of registered place of residence, and informationabout an individual's legal status. The pre-registered biologicalpattern information storage unit 62 uses for example a magnetic harddisk drive unit, semiconductor memory, and the like as a means forstoring information.

(Method of Unique Region Detection Processing)

Hereinbelow, the configuration of the inside of the unique regiondetecting unit 61 and the method of unique region detection processingare described. Here, the target biological pattern information isinformation of a fingerprint image.

FIG. 3 is a block diagram that shows the schematic functionconfiguration of the inner portion of the unique region detection unit61. As shown in FIG. 3, the unique region detecting unit 61 includes acommon function group, an abnormal pattern detection function, anabnormal ridge direction detection function, a ridge destructiondetection function, and a cutout processing detection function. Thecommon function group includes a ridge direction detecting unit 70, aridge pitch detecting unit 71, a ridge strength detecting unit 72, and adirectional singular point detecting unit 73. The operation of theunique region detecting unit 61 using these functions is describedbelow.

The unique region detecting unit 61 first receives data of a fingerprintimage from the detection result obtaining unit 12.

The unique region detecting unit 61 analyzes the fingerprint imagereceived using functions included in the common function group.Specifically, the ridge direction detecting unit 70 detects the ridgedirection in a fingerprint image. The ridge pitch detecting unit 71detects the ridge pitch in a fingerprint image. The ridge strengthdetecting unit 72 detects the ridge strength in a fingerprint image. Thedirectional singular point detecting unit 73 detects the singular pointin a fingerprint image. The unique region detecting unit 61 may detectonly any one of ridge direction, ridge pitch, ridge strength, andsingular point rather than all thereof. The processing that detects theridge pitch, ridge strength, and singular point from a fingerprint imageis a feature extraction process in general fingerprint authenticationtechnology, and can be performed using prior art.

A ridge direction is the direction in which a ridge heads. Ridge pitchis the width between parallel ridges (the distance from one ridge toanother parallel and adjacent ridge). Ridge strength is a degreeexpressing ridge-likeness as information obtained from an image. Asingular point is a portion in a fingerprint image at which a ridgebecomes discontinuous.

The unique region detecting unit 61 initially extracts ridge direction,ridge pitch, and ridge strength from the fingerprint image that has beenreceived using the Gabor filter. Specifically, the unique regiondetecting unit 61, for each pixel included in the fingerprint image,applies Gabor filters with the direction and pitch changed in stages.The direction and pitch of that filter from which the highest absolutevalues are obtained among the Gabor filters that are applied areregarded as the direction and pitch of the ridge in that pixel. Also,the unique region detecting unit 61 extracts the absolute value of thefilter application value at that time as ridge strength.

The unique region detecting unit 61 detects the singular points in afingerprint image. Among singular points there exist a directional shapecalled a delta and a direction shape called a core. Among these, thecore type can be further classified into a circular core and asemicircular core. A circular core is a core in which the ridges rotate360° in the range of the singular point. A semicircular core is a corein which the ridges rotate 180° in the range of the singular point. Asthe method of detecting singular points, the unique region detectingunit 61 uses prior art. As an example, a method of detecting singularpoints is disclosed in a document [Asker Michel Bazen, “Fingerprintidentification: Feature Extraction, Matching, and Database Search”,Twente University Press, 2002]. The unique region detecting unit 61stores the number of detected circular cores, semicircular cores anddeltas per finger, and the position (coordinates) of each of thesingular points for processing at a later stage. The unique regiondetecting unit 61 detects the direction of the pattern in a singularpoint (for example, in the case of a semicircular core, whether the sideon which the ridge is open is the upper side or lower side of thefinger), and stores the information for processing at a later stage.

In addition to the example of the prior art mentioned above, the uniqueregion detecting unit 61 may also use another system. In order toimprove accuracy, the unique region detecting unit 61 may jointly use aseparate means for correcting extraction errors in the ridge directionand ridge pitch.

Next, the unique region detecting unit 61 performs a process fordetecting four kinds of unique regions in a fingerprint image. The fourkinds are (1) abnormal pattern, (2) abnormal ridge direction, (3) ridgedestruction, and (4) cutout process. The characteristics of afingerprint having these four kinds of abnormalities and methods fordetection thereof are described below.

((1) Abnormal Pattern Detection)

The unique region detecting unit 61 includes an abnormal patterndetection unit 74 as a function for detecting abnormal patterns. Theabnormal pattern detection unit 74 detects an abnormal pattern based onthe number and spatial relationship of the singular points (delta, asemicircular core, circular core) which were detected previously. Normalfingerprint images are classified into four types of fingerprintpatterns based on the pattern of the ridge direction. The four types arearch, loop, whorl, and composite. The number and positional relation ofthe singular points are fixed for each of the fingerprint patterns.

Specifically, in the arch pattern, the number of cores is zero and thenumber of deltas is also zero. That is, the curve of a ridge is smooth.In the loop pattern, the number of semicircular cores is one and thenumber of deltas is one or fewer. In a whorl pattern, either the numberof circular cores is one and the number of deltas is two, or the numberof semicircular cores is two and the number of deltas is two or fewer.In the composite, either the number of semicircular cores is three andthe number of deltas is three or fewer, or there is one circular core,one semicircular core and the number of deltas is three or fewer. In thecase of a normal fingerprint image, there are also predeterminedrestrictions on the spatial relationships of singular points.

Normal fingerprint images have the above-mentioned patterns. Theabnormal pattern detecting unit 74 detects as an abnormal pattern animage with an abnormal pattern that cannot appear in a normalfingerprint image. Specifically, the unique region detecting unit 61detects as an abnormal pattern a fingerprint image that meets any of thefollowing conditions (A) to (F).

Condition (A): When two more circular cores exist

Condition (B): When four or more semicircular cores exist

Condition (C): When two or more cores exist and one or more circularcores exist

Condition (D): When four or more deltas exist Condition (E): When adelta exists above a core (on the side close to the fingertip)

Condition (F): When there are two or more cores whose upper-side issemicircular

That is, the unique region detecting unit 61 detects the singular pointsin ridges contained in a fingerprint image, and detects a unique regionon the basis of the condition of the per-type number of singular pointsand the condition of the spatial relationship among the types ofsingular points.

One of the causes for an abnormal pattern to be detected in afingerprint is a surgical procedure carried out on a finger.

FIGS. 4A to 4C show examples of abnormal patterns in fingerprints. InFIGS. 4A to 4C, the locations indicated by circles are circular cores.Also, the locations indicated by triangles are deltas. The example ofthe fingerprint image shown in FIG. 4A has two circular cores and fourdeltas. That is, this fingerprint image corresponds to the conditions ofthe aforementioned (A) and (D) and is determined by the abnormal patterndetecting unit 74 as having an abnormal pattern. The example of thefingerprint image shown in FIG. 4B has two circular cores and fourdeltas. Also, in the example of the fingerprint image shown in FIG. 4B,a delta exists above two circular cores. That is, this fingerprint imagecorresponds to the conditions of the aforementioned (A), (D), and (E)and is therefore determined by the abnormal pattern detecting unit 74 ashaving an abnormal pattern. The example of the fingerprint image shownin FIG. 4C has two circular cores. That is, this fingerprint imagecorresponds to the aforementioned condition (A) and is thereforedetermined by the abnormal pattern detecting unit 74 as having anabnormal pattern.

The abnormal pattern detecting unit 74, upon detecting an abnormalpattern, outputs the type of abnormality (any of the conditions from (A)to (F) above) and the position and type of the singular point related tothat abnormality.

The abnormal pattern detecting unit 74, upon not detecting an abnormalpattern, outputs information to that effect.

((2) Abnormal Ridge Direction Detection)

The unique region detecting unit 61 detects an abnormal pattern in aridge direction. Abnormal ridge directions also come in a number ofpatterns. The three typical patterns are, for convenience sake, calledthe comb type direction pattern, the ω type direction pattern, and the Xtype direction pattern. In this exemplary embodiment, the unique regiondetecting unit 61 detects the three types of abnormal ridge directionsof the comb type direction pattern, the ω type direction pattern and theX type direction pattern. In the case of fingerprint epidermistransplant surgery having been performed, these abnormal ridge directionpatterns indicate there is a possibility of the transplant being visibleat the boundary of the transplanted epidermis. These patterns are notseen in normal fingerprint images.

FIGS. 5A to 5C show examples of fingerprint images containing anabnormal ridge direction.

FIG. 5A is an example of a fingerprint image having the abnormal ridgedirection called a comb type direction pattern. This comb type abnormalridge direction is a ridge direction pattern that easily occurs near theboundary of a transplanted epidermis when an operation has beenperformed to cut out a fingerprint epidermis with a scalpel and thenreattach the epidermis with the position changed.

FIG. 5B is an example of a fingerprint image having the abnormal ridgedirection called a ω type direction pattern. This ω type abnormal ridgedirection is also a ridge direction pattern that easily occurs near theboundary of a transplanted epidermis when surgery has been performed tocut out a fingerprint epidermis with a scalpel and then reattach theepidermis with the position changed. Also, this ω type direction patternis a pattern that easily occurs when a deep wound has been inflictedwith an edged tool or the like in the arch-shaped portion of afingerprint.

FIG. 5C is an example of a fingerprint image having the abnormal ridgedirection called an X type direction pattern. This X type abnormal ridgedirection is a ridge direction pattern that easily occurs in a suturedportion when the skin is tightly bound with surgical thread.

FIGS. 6A to 6C are conceptual diagrams that schematically show templatesrespectively corresponding to the abnormal ridge direction patterns(comb type, ω type, X type).

FIG. 6A corresponds to the X type direction pattern in a fingerprintimage.

FIG. 6B corresponds to the ω type direction pattern in a fingerprintimage.

FIG. 6C corresponds to the comb type direction pattern in a fingerprintimage.

The inside of the unique region detecting unit 61 includes, in theinterior thereof, a comb type direction pattern detecting unit 75, an ωtype direction pattern detecting unit 76, and an X type directionpattern detecting unit 77 corresponding to each of the above-mentionedabnormal direction patterns. The unique region detecting unit 61, usingthe ridge direction information and ridge strength informationpreviously detected by the aforementioned methods, performs a processfor detection of these abnormal direction patterns.

Below, the process method for detection of each abnormal directionpattern is described.

The comb type direction pattern detecting unit 75, with data of theridge direction and ridge strength detected in advance on the basis ofthe given fingerprint image serving as an input, calculates and outputsa degree expressing comb type direction pattern likeness of thatfingerprint image.

Specifically, the comb type direction pattern detecting unit 75beforehand holds comb type template data which expresses the directionpattern as shown in FIG. 6C in an internal memory. The comb typetemplate data is data obtained on the basis of fingerprint images havingcomb type direction patterns, and is stored in a two-dimensional arraycorresponding to a polar coordinate system. The “i” that is the firstcoordinate of the comb type template data Tk(i,j), which is atwo-dimensional array, corresponds to the displacement angle about thecenter of the template data. “i=1, 2, . . . , M” is satisfied. This “i”is an index value corresponding to each direction when 360°, or alldirections from the center of the fingerprint image, in graduated in(360/M°). With the positive direction of the X axis in the XY orthogonalcoordinate system being 0°, the counterclockwise direction is thepositive direction of the displacement angle. Also, the “j”, which isthe second index, corresponds to the distance from the center of thefingerprint image. “j=1, 2, . . . , N” is satisfied This “j” is an indexvalue corresponding to the distance from the center of the template. Thevalue of each element of Tk(i,j) is a two-dimensional vector (unitvector) value expressing the ridge direction at the portion (smallregion) represented by this polar coordinate.

The comb type direction pattern detecting unit 75, while changing “t”,which is the rotation angle of the template with respect to an arbitrarypixel position (x,y) in a given fingerprint image, calculates thelargest value of the sum of the inner products of the direction vectorsof the ridge direction within a circle of the image. The maximum valueis given by Ek(x,y) with the following equation.

$\begin{matrix}{{{Ek}\left( {x,y} \right)} = {\max\limits_{{t = 1},\ldots,M}\left\{ {\sum\limits_{i = 1}^{N}\frac{{{Tk}\left( {t,i} \right)} \cdot {{Id}\left( {{x + {{dx}(i)}},{y + {{dy}(i)}}} \right)}}{N}} \right\}}} & \left( {{Equation}\mspace{14mu} 1} \right)\end{matrix}$

In equation (1) above, Id(x,y) is the unit vector expressing the ridgedirection at coordinate (x,y) in a fingerprint image. Tk(t,i) is thei-th direction (with rotation angle t) of the comb type template. dx(i)is the x coordinate displacement of the i-th element in the template.dy(i) is the y coordinate displacement of the i-th element in thetemplate.

That is, when the template is rotated 360° at coordinate (x,y) of thefingerprint image, the value of Ek(x,y) calculated by equation (1) isthe correlating value when the correlation between the fingerprint imageand the template is greatest (that is, when t corresponds to such anangle).

Also, the ridge direction (displacement angle) is expressed as anumerical value in a range up to 180° counterclockwise, with thepositive direction of the X axis being 0°. However, since it isnecessary to regard 0° and 180° as essentially being the same direction,the inner product is taken after changing the angle of the directionvector so that the angle with the X axis positive direction (0°direction) is doubled.

The value of Ek(x,y) calculated in equation (1) above is an indicatorexpressing the directional consistency between the fingerprint image andthe template. Moreover, the comb type direction pattern detecting unit75 calculates the comb type evaluation value Wk(x,y) by multiplying bythe ridge strength. The ridge strength expresses thefingerprint-likeness.Wk(x,y)=max(0,Ek(x,y)−C)×Is(x,y)  (Equation 2)

In the above equation, C is a threshold value that is appropriately set.That is, the threshold value C has the action of removing as noise theportion in which the value of Ek(x,y) is equal to or less than C.Is(x,y) is the average value of the ridge strength in the same radius asthe template, centered on the coordinates (x,y).

That is, the evaluation value Wk(x,y) is a value found by subtractingthe threshold value C from the value of Ek(x,y) (whose result becomeszero when negative), and multiplying the difference by the ridgestrength in the vicinity of the coordinates (x,y).

The comb type direction pattern detecting unit 75 outputs the value ofthis Wk(x,y) that has been calculated as a comb type abnormality degree.This comb type abnormality degree is a degree that expresses the combtype direction pattern-likeness.

The ω type direction pattern detecting unit 76 beforehand holds ω typetemplate data which expresses the direction pattern as shown in FIG. 6Bin an internal memory. The data structure of the ω type template data isthe same as the comb type template data. The ω type template data istemplate data that expresses a ridge direction, and is created inadvance based on fingerprint images having an actual ω type directionpattern. The ω type direction pattern detecting unit 76, using the sameprocedure as the calculation procedure of the comb type directionpattern detecting unit 75 described above, calculates the ω typeabnormality degree Wo(x,y) on the basis of a given fingerprint image andthe aforementioned ω type template data.

The X-type direction pattern detecting unit 77 beforehand holds X-typetemplate data which expresses the direction pattern as shown in FIG. 6Ain an internal memory. The data structure of the X-type template data isthe same as the comb type template data. The X-type template data istemplate data that expresses a ridge direction, and is created inadvance based on fingerprint images having an actual X-type directionpattern. The X-type direction pattern detecting unit 77, using the sameprocedure as the calculation procedure of the comb type directionpattern detecting unit 75 described above, calculates the X-typeabnormality degree Wx(x,y) on the basis of a given fingerprint image andthe aforementioned X-type template data.

The unique region detecting unit 61 determines whether the fingerprintimage is an abnormal ridge direction fingerprint by whether therespective maximum values of the comb type abnormality degree Wk(x,y)output by the comb type direction pattern detecting unit 75, the ω typeabnormality degree Wo(x,y) output by the ω type direction patterndetecting unit 76, and the X-type abnormality degree Wx(x,y) output bythe X-type direction pattern detecting unit 77 exceed the predeterminedthreshold value. When the value exceeds the threshold value, the uniqueregion detecting unit 61 determines that the fingerprint image is anabnormal ridge direction fingerprint (that is, the comb type directionpattern, the ω type direction pattern, or the X-type direction pattern).Otherwise, the fingerprint image is determined to not be an abnormalridge direction fingerprint.

As another method, the unique region detecting unit 61 may determinewhether the fingerprint image is an abnormal ridge direction fingerprintby whether the sum of each maximum value of the comb type abnormalitydegree Wk(x,y) output by the comb type direction pattern detecting unit75, the ω type abnormality degree Wo(x,y) output by the ω type directionpattern detecting unit 76, and the X-type abnormality degree Wx(x,y)output by the X-type direction pattern detecting unit 77 exceeds apredetermined threshold value. When that value exceeds the thresholdvalue, the unique region detecting unit 61 determines the fingerprintimage to be an abnormal ridge direction fingerprint. Otherwise, theunique region detecting unit 61 determines the fingerprint image to notbe an abnormal ridge direction fingerprint.

That is, the unique region detecting unit 61 obtains the ridge directioninformation for every part contained in a fingerprint image. The uniqueregion detecting unit 61 finds an evaluation value showing the degree towhich the ridge direction information has an abnormal ridge directionpattern based on the correlation between the ridge direction informationand templates of the abnormal ridge direction patterns stored in advance(the comb type direction pattern, the ω type direction pattern, and theX-type direction pattern). Moreover, the unique region detecting unit 61detects as a unique region a portion corresponding to the ridgedirection information when that evaluation value is equal to or greaterthan the predetermined threshold value.

The unique region detecting unit 61, upon determining the fingerprintimage to be an abnormal ridge direction fingerprint, outputs informationof the position of that unique region.

On the basis of an actual fingerprint database, weighting may also beperformed in a probability distribution of the aforementioned evaluationvalues (comb type abnormality degree, ω type abnormality degree, andX-type abnormality degree). Thereby, it is possible to further increasethe determination accuracy by the unique region detecting unit 61.

In the present exemplary embodiment, the unique region detecting unit 61includes, in the interior thereof, the comb type direction patterndetecting unit 75, the ω type direction pattern detecting unit 76, andthe X-type direction pattern detecting unit 77, and detects abnormalridge directions respectively corresponding thereto, but is not limitedto such a constitution. A configuration is also possible in which someof these units are omitted.

Conversely, the unique region detecting unit 61 may include additionaldirection pattern templates, and thereby detect abnormal ridgedirections other than these three types. As one example, a configurationthat can detect patterns in which the angle of the comb type, ω type andX type is slightly changed, and a configuration can detect several typesof patterns by changing the radius of the template are possible.

The method of detecting a unique region on the basis of the number ofsingular points and the positional relation between the singular pointsdescribed in “(1) Abnormal pattern detection” above is a valid methodwhen a clear image of the overall fingerprint is obtained. In contrast,the method that uses an evaluation value based on a template ((2)Abnormal ridge direction detection) has the advantage of detection of anabnormal fingerprint with a specific shape being possible even when onlya partial image of a fingerprint is obtained.

((3) Ridge Destruction Detection)

The unique region detecting unit 61 also has a function to detectdestruction of ridges in a fingerprint. Specifically, the unique regiondetecting unit 61 includes, in the interior thereof, a ridge destructiondetecting unit 78. The unique region detecting unit 61 performsprocessing for detecting each of these abnormal direction patterns usingridge direction information and ridge strength information alreadydetected by the aforementioned methods.

FIG. 7 is an example that conceptually shows a fingerprint imageincluding ridge destruction. In the example of a fingerprint image shownin FIG. 7, some of the originally continuous ridges are discontinuous,with a pattern of dots existing at that portion. In FIG. 7, the portionindicated by the elliptical frame is a portion that includes ridgedestruction. Such ridge destruction may be produced from a burn ordamage from a chemical agent.

The ridge destruction detecting unit 78 obtains data of the ridgedirection image obtained by the aforementioned method. The data of thisridge direction image contains data of the ridge direction in eachpixel. The ridge destruction detecting unit 78 performs a directionalsmoothing process over a large area. This directional smoothing processis a process that corrects a portion in a fingerprint image including aridge direction incorrectly detected due to reasons such as noise to thecorrect ridge direction. The directional smoothing process itself isrealizable with statistical processing on pixel values of ridgedirection image data. A directional smoothing process is for example aprocess that takes the most frequent value of a directional component ofa region within a definite range or takes the average of directionvectors of a region within a definite range.

FIG. 8 and FIG. 9 are schematic diagrams for showing actual examples ofthe aforementioned directional smoothing process. FIG. 8 is ridgedirection image data obtained for the example of the fingerprint imageof FIG. 7. In FIG. 7, the ridge directions are in a discontinuous stateat the portion where the ridges are destroyed. Ridge direction imagedata for such a portion is easily influenced by noise. This is becausethe directions of the detected ridges are not stabilized. Therefore, inthe center portion of FIG. 8, the ridge directions are not constant butrather random. FIG. 9 is an image of the result of performing thedirectional smoothing process on the ridge direction image of FIG. 8.The ridge destruction detecting unit 78, by performing a directionalsmoothing process over a large area, can obtain a direction image shownin FIG. 9 that smoothly changes.

The ridge destruction detecting unit 78 finds the angle differencebetween an initial ridge direction and the ridge direction aftersmoothing for every part within a direction image. When the angle(direction) has changed by a predetermined amount or more, that is, whenthe absolute value of the angle difference is a predetermined amount ormore, the ridge destruction detecting unit 78 extracts this portion as aridge destruction candidate region. Portions other than the ridgedestruction marks due to burns or chemicals may be extracted as ridgedestruction candidate regions. For example, portions such as wrinklesand blemishes of seniors fall under this type. These wrinkles andblemishes, unlike portions of burn and chemical scars, have a finelinear shape. Therefore, the ridge destruction detecting unit 78 repeatsimage processing called expansion and contraction on the ridgedestruction candidate region extracted above to perform removal of suchlinear (or point-like) detailed marks.

Finally, the ridge destruction detecting unit 78 finds and outputs anevaluation value for ridge destruction detection by calculating thetotal of ridge strengths already obtained by the aforedescribedprocessing for this ridge destruction candidate region. The uniqueregion detecting unit 61 determines the fingerprint to be one havingridge destruction marks when the evaluation value of the ridgedestruction output by the ridge destruction detecting unit 78 is equalto or greater than a predetermined threshold. In other cases, the uniqueregion detecting unit 61 determines the fingerprint to be a fingerprintwithout ridge destruction marks.

That is, the unique region detecting unit 61 obtains the ridge directioninformation of every portion contained in a fingerprint image. Theunique region detecting unit 61 also obtains smoothed ridge directioninformation by performing the directional smoothing process based on theridge direction information of surrounding portions of that portion foreach part of the ridge direction information. When the (absolute valueof the) difference between the ridge direction information and thesmoothed ridge direction information is larger than a predeterminedthreshold, the unique region detecting unit 61 detects the regioncorresponding to that portion as a unique region.

The unique region detecting unit 61, upon determining that thefingerprint is one with a ridge destruction mark, outputs information onthe position of that unique region.

There are not only cases of ridge destruction due to burns or chemicals,but also cases of ridge destruction due to aging deterioration over manyyears and being engaged in physical work involving the hands. In thecase of such natural destruction, all the ridges of a finger aredestroyed, not just a specified portion. In order to distinguish betweensuch natural destruction on all regions and partial destruction due toburns and chemicals (including intentional destruction), the uniqueregion detecting unit 61 may determine whether or not a fingerprintportion other than the ridge destruction candidate region has an imageof high-quality ridges. Thereby, it is possible to detect only ridgedestruction by the specified condition.

The unique region detecting unit 61 may simultaneously determine whetheror not a ridge destruction mark exists in the fingerprint centerportion. Since the fingerprint center portion is a portion having alarge influence on the determination in fingerprint collation, ridgedestruction is sometimes performed intentionally. Thereby, it ispossible to detect only ridge destruction of a specific location.

((4) Cutout Processing Detection)

The unique region detecting unit 61 also has a function to detect cutoutprocessing of a fingerprint. Specifically, the unique region detectingunit 61 includes a cutout processing detecting unit 79. The cutoutprocessing detecting unit 79 determines the existence of a cutoutprocess in relation to the input fingerprint image on the basis of achange in the ridge pitch (ridge interval), as described below. This isbecause, in the case of a fingerprint that has been subjected to acutout process from an operation, due to suturing while pulling the skinaround the surgical wound, the pitch of ridges at a specific region andthe pitch of ridges in a specific direction may change locally.

FIG. 10 and FIG. 11 are schematic diagrams for describing the cutoutprocess of a fingerprint. FIG. 10 shows an example of a fingerprintimage prior to a cutout process. FIG. 11 shows an example of afingerprint image after a cutout process in relation to the fingerprintshown in FIG. 10. One example of a cutout process by means of anoperation is a method that entails applying a scalpel at the portionindicated by a diamond shape in the center of the fingerprint of FIG.10, cutting out the inner epidermis, and suturing the diamond-shapedcentral portion while pulling the skin laterally, that is, in thehorizontal direction so as to close the diamond shape that has been cutout.

In the case of having carried out a cutout operation that alters thefingerprint in the manner of FIG. 11, with regard to the ridges on theleft side of FIG. 11 in a direction perpendicular to the cutoutdirection (that is, in the present example, the ridges running in thehorizontal direction, the portion denoted by “A” in FIG. 11), the ridgepitch does not change as a result of the pulling. On the other hand, asfor the ridges on the right side of FIG. 11 in a direction parallel withthe cutout direction (that is, in the present example, the ridgesrunning in the vertical direction, the portion denoted by “B” in FIG.11), the characteristic is observed of the ridge pitch becoming widerthan the original pitch.

The method of the detection process by the cutout processing detectingunit 79 is as follows.

The cutout processing detecting unit 79 first detects the position of awound resulting from a cutout process. Specifically, a line segment of adefinite length is generated at an arbitrary angle from an arbitrarypixel in an image, and in an image portion of a fixed-distance range (1to 16 pixel portion) from line segments on both sides of that linesegment, the ridge direction difference and ridge pitch difference areadded together. The coordinates (x,y) and angle (t) where that additionvalue becomes a maximum is made a candidate of the wound position.

Next, the cutout process detecting unit 79 calculates two types ofcutout process evaluation values with respect to a rectangular region ofa predetermined side on both sides of the wound (that is, region R1 andregion R2, respectively). The first evaluation value Wc1 is an index forchecking whether or not the ridge pitch in the same direction as thewound is wider. The second evaluation value Wc2 is an index for checkingwhether or not the ridge pitches on both sides of the wound differ. Thecutout process detecting unit 79 calculates Wc1 and Wc2 by the followingequations.

$\begin{matrix}{{{Wc}\; 1} = {\max\limits_{{R = {R\; 1}},{R\; 2}}\left\{ {\frac{\mspace{11mu}\left( \begin{matrix}{90 - {{angle}\mspace{14mu}{difference}\mspace{14mu}{between}}} \\{{average}\mspace{14mu}{direction}\mspace{14mu}{in}\mspace{14mu} R\mspace{14mu}{and}\mspace{14mu} t}\end{matrix}\; \right)}{90} \times {\max\left( {0,\frac{{{average}\mspace{14mu}{pitch}\mspace{14mu}{in}\mspace{14mu} R} - {{fingerprint}\mspace{14mu}{average}\mspace{14mu}{pitch}}}{{fingerprint}\mspace{14mu}{average}\mspace{14mu}{pitch}}} \right)} \times {average}\mspace{14mu}{strength}\mspace{14mu}{in}\mspace{14mu} R} \right\}}} & \left( {{Equation}\mspace{14mu} 3} \right) \\{{{Wc}\; 2} = {\frac{{{{average}\mspace{14mu}{pitch}\mspace{14mu}{in}\mspace{14mu} R\; 1} - {{average}\mspace{14mu}{pitch}\mspace{14mu}{in}\mspace{14mu} R\; 2}}}{{fingerprint}\mspace{14mu}{average}\mspace{14mu}{pitch}} \times {\min\left( {{{average}\mspace{14mu}{strength}\mspace{14mu}{in}\mspace{14mu} R\; 1},{{average}\mspace{14mu}{strength}\mspace{14mu}{in}\mspace{14mu} R\; 2}} \right)}}} & \left( {{Equation}\mspace{14mu} 4} \right)\end{matrix}$

That is, the evaluation value Wc1 is, in relation to each of regions R1and R2, the product of the degree in which the ridge direction in theregion matches “t”, the degree to which the ridge pitch in the region iswider than the ridge pitch of the entire fingerprint (being 0 whennarrower than the ridge pitch of the entire fingerprint), and the ridgestrength in the region, and is the greater of the two (the valuerelating to region R1 or the value relating to region R2).

Also, the evaluation value Wc2 is the product of the degree to which thedifference between the ridge pitches of regions R1 and R2 is large andthe ridge strength (smaller one of the strengths of regions R1 and R2).

The average direction in the above equation is calculated by taking aweighted mean using a weighting by ridge strength generated by the ridgestrength detecting unit 72, in relation to direction data generated bythe ridge direction detecting unit 70. The average pitch in the aboveequation is calculated by taking a weighted mean using a weighting byridge strength generated by the ridge strength detecting unit 72, inrelation to pitch data generated by the ridge pitch detecting unit 71.

The determination by the evaluation values Wc1 and Wc2 calculated by thecutout process detecting unit 79 is valid when the wound position iscorrectly detected. However, depending on the fingerprint, cases existin which the location of the cutout process is obscure, and the woundposition is not clearly known. To deal with such cases, a method isjointly used to detect whether or not an unnaturally wide pitch portionexists in the entire fingerprint, without utilizing the wound positiondetected by the cutout process detecting unit 79. For that reason, thefollowing evaluation values Wc3 and Wc4 are used as indices. Evaluationvalue Wc3 is an index for checking whether or not an abnormally widepitch portion exists. Evaluation value Wc4 is an index for checkingwhether the pitch in a specific direction is widened. The cutout processdetecting unit 79 calculates Wc3 and Wc4 by the following equations.

$\begin{matrix}{{{Wc}\; 3} = \frac{\begin{matrix}{{sum}\mspace{14mu}{total}\mspace{14mu}{of}\mspace{14mu}{ridge}\mspace{14mu}{strengths}\mspace{14mu}{which}\mspace{14mu}{is}\mspace{14mu} 1.5\mspace{14mu}{times}\mspace{14mu}{or}} \\{{more}\mspace{14mu}{fingerpring}\mspace{14mu}{average}\mspace{14mu}{pitch}}\end{matrix}}{\begin{matrix}{{sum}\mspace{14mu}{total}\mspace{14mu}{of}\mspace{14mu}{ridge}\mspace{14mu}{strength}\mspace{14mu}{of}\mspace{14mu}{entire}} \\{fingerprint}\end{matrix}}} & \left( {{Equation}\mspace{14mu} 5} \right) \\{{{Wc}\; 4} = \frac{\begin{matrix}{{average}\mspace{14mu}{pitch}\mspace{14mu}{in}\mspace{14mu}{direction}\mspace{14mu}{Dm} \times} \\{{average}\mspace{14mu}{strength}\mspace{14mu}{in}\mspace{14mu}{direction}\mspace{14mu}{Dm}}\end{matrix}}{{average}\mspace{14mu}{pitch} \times {average}\mspace{14mu}{strength}}} & \left( {{Equation}\mspace{14mu} 6} \right)\end{matrix}$

In the equation for Wc4, Dm is a direction in which the average pitchbecomes a maximum.

That is, the evaluation value Wc3 is a ratio value that expresses theratio of locations with a wide ridge pitch in the entire fingerprint(with 1.5 times the average pitch in the entire fingerprint being thebasis) and takes into consideration the ridge strength.

The evaluation value Wc4 is a ratio value that expresses the ratio ofpitch width in a specified ridge direction (the direction in which theaverage pitch becomes a maximum) in the entire fingerprint and takesinto consideration the ridge strength.

Finally, the cutout process detecting unit 79 outputs the four kinds ofevaluation values Wc1, Wc2, Wc3, Wc4 described above. The unique regiondetecting unit 61 determines whether or not a cutout process is includedin the fingerprint image depending on whether or not the respectivevalues of these evaluation values Wc1, Wc2, Wc3, Wc4 are equal to orgreater than predetermined threshold values. The unique region detectingunit 61 multiples each of these evaluation values Wc1, Wc2, Wc3, Wc4 bya predetermined weighting to find a weighted average, and depending onwhether or not that weighted average value is equal to or greater than apredetermined threshold value, may determine whether a cutout process isincluded in the fingerprint image.

That is, the unique region detecting unit 61 obtains ridge directioninformation and ridge pitch information for each portion included in thefingerprint image. The unique region detecting unit 61, on the basis ofthe ridge direction information and ridge pitch information, finds anevaluation value that becomes a greater value the more the ridgedirection difference and the ridge pitch difference between adjacentregions in the fingerprint image increase. Moreover, the unique regiondetecting unit 61 detects adjacent regions as being a unique region dueto a cutout process when the evaluation value is greater than apredetermined threshold.

The unique region detecting unit 61, upon determining the fingerprint tobe one having a cutout process, outputs information of the position ofthat unique region.

Generally, in a normal fingerprint, the ridge pitch in the horizontaldirection (shortwise direction a finger) near the distal interphalangealjoint at the bottom of a fingerprint exhibits a tendency to be widerthan the ridge pitch in other regions. Based on this, in theaforementioned process, the region in which the ridges are horizontal atthe bottom of a fingerprint may be excluded from the calculation of theaforementioned evaluation values Wc1, Wc2, Wc3, Wc4. By the cutoutprocess detecting unit 79 calculating the evaluation values in this way,it is possible to further raise the determination accuracy.

In cases in which people who have had their fingerprints extracted donot desire personal authentication, sometimes they make a fingerprintwhile intentionally twisting their fingerprint. In such cases, due tothe pulling that results from the twisting action, a tendency isobserved for the pitch in a specified region and a specified directionof the fingerprint to widen. The evaluation values Wc3 and Wc4, which donot use a wound location, can also be used for the purpose of detectinga fingerprint pressed in a state not suited to authentication due to atwisting action or the like.

With the configuration of the second exemplary embodiment, thebiological pattern information processing device 2, on the basis ofinformation obtained by the detection result obtaining unit 12, canperform a collation process in accordance with the presence of a uniqueregion. Also, it is possible to perform a collation process inaccordance with the position of a unique region.

(Modification)

As a modification of the second exemplary embodiment, the displaycontrol unit 121 performs control so as to display the type of theunique region in accordance with information on the unique region thathas been received. The type of a unique region means for example thetype of abnormality such as an abnormal pattern, an abnormal ridgedirection, ridge destruction, a cutout process described above.Specifically, the display control unit 121 according to thismodification displays, as added information, information on the type ofdamage (pattern information) near a region that displays a fingerprintimage. As an example, the display control unit 121 displays a calloutarrow at the location of a unique region detected in a fingerprintimage, and displays in the callout text indicating the type of damage.In another example, the display control unit 121 displays a mark or iconindicating the type of damage marks at the location of a unique regiondetected in a fingerprint image.

With the configuration such as this modification, a user visuallyconfirming an actual fingerprint image can find out what pattern theunique region has. Accordingly, misunderstandings on the part of theuser have less of a tendency to occur.

Third Exemplary Embodiment

Next, the third exemplary embodiment will be described. The descriptionthat follows will focus on matter peculiar to the third exemplaryembodiment, with the description of matter in common with the precedingexemplary embodiments being omitted.

FIG. 12 is a block diagram that shows the schematic functionconfiguration of the biological pattern information processing deviceaccording to the third exemplary embodiment. As shown in FIG. 12, thebiological pattern information processing device 3 according to thethird exemplary embodiment includes the biological pattern informationobtaining unit 11, the detection result obtaining unit 12, a repairingunit 214, the collating unit 116, and the display control unit 121.

The biological pattern information obtaining unit 11, the detectionresult obtaining unit 12, a repairing unit 214, the collating unit 116,and the display control unit 121 have the same functions as eachcorresponding function in the first and second exemplary embodiments.The characteristic of the biological pattern information processingdevice 3 according to the third exemplary embodiment is the point ofincluding the repairing unit 214.

The repairing unit 214, for biological pattern information included in aunique region of biological pattern information obtained by theinformation obtaining unit 11, repairs damage of the biologicalinformation that has occurred at that unique region.

The collating unit 116 in the present exemplary embodiment then performsa collation process treating the biological pattern information repairedby the repairing unit 214 as a region other than a unique region.

Next, the process by the repairing unit 214 will be described. Therepairing unit 214 performs a process of repairing a fingerprint with aunique region produced by an operation called “Z-plasty”. Z-plasty issurgical technique in which a scalpel cuts a Z shape in the epidermis ofa fingerprint, and the two triangular portions of skin that are producedby the Z-shaped incision are swapped and sutured. Since positionalchange of a fingerprint feature quantity occurs when this kind ofsurgery is performed, collation as is with the fingerprint prior tosurgery is difficult or impossible.

FIG. 13 and FIG. 14 are schematic diagrams that show examples of afingerprint image for describing a Z-plasty operation. FIG. 13 shows animage before execution of a Z-plasty operation. FIG. 14 shows an imageafter execution of a Z-plasty operation. As described above, due to theswapping and suturing of the two triangular skin portions produced bythe Z-shaped incision, the fingerprint image shown in FIG. 14 has apattern that is ordinarily impossible.

The fingerprint image shown in FIG. 14 is an abnormal fingerprint. Therepairing unit 214 performs a process that repairs a fingerprint imageas shown in FIG. 14 produced by Z-plasty, that is, performs a process onthe image, and performs a process for returning the image to theoriginal (pre-operation) fingerprint image shown in FIG. 13.

FIG. 15 is a block diagram that shows the schematic functionconfiguration of the interior of a repairing unit 214. As shown in FIG.15, the repairing unit 214 includes in the interior thereof a damagedarea detecting unit 91 and a Z-plasty operation fingerprint restoringunit 92.

Hereinbelow, the method of the process by the repairing unit 214 will bedescribed.

The damaged area detecting unit 91 detects marks resulting from anoperation from the fingerprint image, and outputs an abnormality degreeimage expressing the abnormality as an image. As an example, theabnormality degree image expresses the abnormality in the image withgradations.

The damaged area detecting unit 91 uses as the abnormality degree any ofa comb type evaluation value Wk (x,y), an ω type evaluation value Wk(x,y), or an X-type evaluation value Wk (x,y) calculated by the uniqueregion detecting unit 61 described above. The damaged area detectingunit 91 may be configured to receive these evaluation values from theunique region detecting unit 61, or the damaged area detecting unit 91may be configured to calculate these evaluation values by the samemethod. The damaged area detecting unit 91 may also use anotherevaluation value (for example, a value expressing the degree ofdirection change or pitch change described above) as the abnormalitydegree. The damaged area detecting unit 91 may also use as theabnormality degree a weighted average value obtained by weighting eachof these evaluation values and taking an average. The damaged areadetecting unit 91 then creates the abnormality degree image using any ofthe abnormality degrees described here.

The Z-plasty operation fingerprint restoring unit 92 receives the twoimages of a fingerprint image and an abnormality degree image created bythe damaged area detecting unit 91 and outputs a fingerprint restorationimage after the processing.

Specifically, the Z-plasty operation fingerprint restoring unit 92 firstapplies a half conversion to the abnormality degree image. By this halfconversion, the Z-plasty operation fingerprint restoring unit 92 detectsa linear component in the abnormality degree image. The Z-plastyoperation fingerprint restoring unit 92 detects three linear components(a first candidate to a third candidate) in which portions with a highdegree of abnormality (dark portions when the abnormality degree isrepresented as a greyscale image) are arranged linearly. When the threelinear components of the first candidate to third candidate form theshape of a “Z”, the Z-plasty operation fingerprint restoring unit 92determines that the fingerprint is one in which Z-plasty has beenapplied.

The Z-plasty operation fingerprint restoring unit 92 uses the followingcondition (1) to condition (3) to determine whether or not the threelinear components of the first component to the third component form a“Z” shape. The condition for being determined to be a “Z” shape is thatall of the following conditions (1) to (3) are met. Note that incondition (1) to condition (3), the three linear components that are thefirst candidate to the third candidate express straight lines (linesections) A, B, C.

Condition (1): The two straight lines A and B whose mutual directions(angles) are closest are nearly parallel. Specifically, the differencein the direction of straight line A and straight line B is 15° or less,and straight line A and straight line B do not intersect within therange of the image.

Condition (2): The straight line C other than A and B intersects thestraight lines A and B with a difference in direction (angle) of 20°more and 60° or less within the range of the image.

Condition (3): The average value of the pixel values in the abnormalitydegree image on the straight lines (linear sections) A, B, C is for eachlinear section (all three) equal to or greater than a predeterminedthreshold value.

FIG. 16 is a schematic diagram for describing a method of restoring afingerprint that underwent a Z-plasty operation. In the case of an inputfingerprint image being determined to be a fingerprint that underwent aZ-plasty operation, the Z-plasty operation fingerprint restoring unit 92restores the image to the pre-operation image by the method describedbelow (step (1) to step (6)) and outputs the obtained pre-operationimage. FIG. 16 shows the three candidates (straight lines A, B, C) oflinear components in the abnormal value image detected in the abovedetermination. FIG. 16 shows points D, E, F, G used in the restorationprocedure below.

Step (1): Let the intersection of straight line A and straight line B beD, and let the intersection of straight line C and straight line B be E.

Step (2): Let the foot of a perpendicular drawn from the intersectionpoint E to straight line A (the intersection point between thatperpendicular line and straight line A) be point F.

Step (3): Let the foot of a perpendicular drawn from the intersectionpoint D to straight line B (the intersection point between thatperpendicular line and straight line B) be point G.

Step (4): Copy the portion surrounded by the triangle FDE (firstpolygon) in the input image onto the triangle FGE of the output image byan affine transformation.

Step (5): Copy the portion surrounded by the triangle DEG (secondpolygon) in the input image onto the triangle DFG of the output image byan affine transformation.

Step (6): Copy as is the regions other than the portions copied in theaforementioned steps (4) and (5) from the input image to the outputimage.

That is, on the basis of the correlation between the ridge directioninformation of each portion included in the fingerprint image and atemplate of an abnormal ridge direction pattern held in advance, therepairing unit 214 finds for each portion an evaluation value thatexpresses the degree to which the ridge direction information has theabnormal ridge direction pattern, and extracts a straight line componentof the evaluation value in the fingerprint image. The repairing unit 214repairs the damage by mutually replacing the fingerprint images includedin the first polygon and second polygon defined on the basis of thestraight line components (however, when the shape of the replacementdestination polygon differs from the original polygon shape, shapeadjustment is performed by an affine transformation or the like).

It is not necessarily guaranteed that the points F and G used in theaforementioned method will completely agree with the cutout portions inan actual operation. However, the feature quantities of the fingerprintimage on the triangle FGE and the triangle DFG respectively used in thesteps (4) and (5) can be expected to approach the positions in thepre-operation fingerprint. That is, the possibility that collation withthe pre-registered biological pattern information in the collating unit116 will succeed increases due to this repair process by the repairingunit 214.

Also, in the case of handling an operated fingerprint in which theprocessed portion is clear, the repairing unit 214 may correct thecoordinate position of the point F that serves as a processing startpoint by performing image matching (ridge matching) along the boundariesof line segment DF and line segment DE of the deformed portion.Similarly, the coordinate position of the point G that serves as aprocessing start point may be corrected by performing image matchingalong the boundaries of line segment EG and line segment ED of thedeformed portion.

(Modification 1 of Repairing Unit)

The process of the repairing unit 214 may be carried out as in thefollowing modification.

The case will be described of an input fingerprint image beingdetermined to be one that includes cutout process damage on the basis ofthe evaluation values Wc1 and Wc2 calculated by the cutout processingdetecting unit 79 described above. In this case, the repairing unit 214detects a rectangular region of which the side on the wide-pitch side ofthe detected wound has a wide pitch, calculates the product of the widthof this region and the pitch change differential within the rectangle,and estimates this to be the width of the cutout portion. Thereby, byperforming image deformation so as to insert the diamond-shaped regionin the center of FIG. 10 as a blank portion within the detectedrectangular region of the image of FIG. 11 it is possible to restore thefingerprint periphery outside the diamond shape.

(Modification 2 of Repairing Unit)

As another modification of the repairing unit 214, a process may becarried out so as to use the repairing unit 214 a described below. Therepairing unit 214 a of this modification does not restore apre-operation fingerprint by deformation or the like, but ratherexcludes the portion of a fingerprint in which processing has beenperformed, extracts only the portion in which processing has not beenperformed, and outputs the extracted result as the restored image. Thatis, the repairing unit 214 a cuts out the portion that has not beenprocessed by an operation or the like.

FIG. 17 is a block diagram that shows the schematic functionconfiguration of the repairing unit 214 a according to thismodification. As shown in FIG. 17, the repairing unit 214 a according tothis modification includes a damaged area detecting unit 93 and adamaged area removing unit 94.

An example of the function of the damaged area detecting unit 93 is thesame as the function of the damaged area detecting unit 91 describedabove. The damaged area detecting unit 93 may additionally include afunction for detecting an abnormally wide pitch region and a functionfor detecting a ridge damage region (a function similar to the ridgedestruction detecting unit 78). Thereby, it is possible to detect adamaged area in consideration of abnormality degree image information.

The damaged area removing unit 94 decides the exclusion region to beexcluded as a damaged area by any of the methods given below (method (1)to method (4)) based on the abnormality degree image generated by thedamaged area detecting unit 93. Moreover, the damaged area removing unit94, after filling in the excluded region in the fingerprint image withthe background color, outputs that image.

Method (1): A region with an abnormality degree equal to or greater thana predetermined threshold value and within 16 pixels of that vicinity(the value of “16” here may be changed to another value) are made anexclusion region.

Method (2): A region with an abnormality degree equal to or greater thana predetermined threshold value is extracted and, by expansion andcontraction processing of the image, made an exclusion region includinga region in an abnormal region.

Method (3): A region with an abnormality degree equal to or greater thana predetermined threshold value is made an abnormal region, and afingerprint position separated the greatest distance from that abnormalregion is detected. From that position, a region within a predetermineddistance in which the ridge direction and ridge pitch continuouslychange (there is no abnormal discontinuity) is made the valid region. Aportion other than that valid region is made the exclusion region.

Method (4): A region with an abnormality degree equal to or greater thana predetermined threshold value is made an abnormal region, and afingerprint position separated the greatest distance from that abnormalregion is detected. In a circle centered on that position, having as itsradius the distance from that position to the abnormal region, theoutside of the circle is made the exclusion region.

That is, the repairing unit 214 a repairs damage by removing from theentire fingerprint image information of the fingerprint image belongingto the exclusion region defined on the basis of a unique region.

Whether to adopt a method from the aforementioned methods (1) to (4) canbe controlled by a parameter given from outside, for example. As anotherexample, method (4) is applied with the highest priority, and in theevent that the region (width) of the fingerprint image required for thecollation process is not obtained as a result, method (3) is applied,and likewise method (2) and method (1) in that order.

Although the process by the Z-plasty operation fingerprint restoringunit 92 corresponds to only fingerprints with damage due to an operationof a specific method, when surgical scars are not clearly visible, thereis a possibility that restoration of the pre-operation fingerprint maynot be possible. In such a case, by excluding the portion at which afingerprint process was performed by the method using the damaged arearemoving unit 94, there is the advantage of being able to performcollation with the person's fingerprint prior to the process.

Also when based on this modification, the repairing unit 214 a, in thesense of removing information of a damaged portion, is an example of thecase of, for biological pattern information included in a unique regionamong biological pattern information acquired by the biological patterninformation obtaining unit 11, repairing damage to the biologicalpattern information that occurred in the unique region.

It is not necessarily guaranteed that the process by the repairing unit214 (or the modification thereof) (that is, the process of restoring tothe pre-operation state a fingerprint that underwent a Z-plastyoperation or excluding a damaged area) will accurately restore thepre-operation fingerprint. For example, it is possible that a normalfingerprint of a finger with no operation history may be judged ashaving undergone an operation due to an incorrect determination, andthereby end up being processed. However, it is possible to lower therisk of a drop in the authentication rate by for example the collatingunit 116 collating both the fingerprint image prior to processing by therepairing unit 214 (of the modification thereof) and the post-processfingerprint image with the pre-registered biological pattern informationstorage unit 62. When collating both pre- and post-processing imageswith the pre-registered biological pattern information storage unit 62,the case of either fingerprint image matching a pre-registeredbiological pattern can be regarded as agreement with the pre-registeredbiological pattern.

As a result of the processing by the repairing unit 214 (of themodification thereof), there is the risk of the fingerprint image afterthe restoration process matching another person's fingerprint. However,provided the operator does not make a final judgement based solely onthat match but instead performs a separate confirmation using a meansother than a fingerprint (for example, a facial photograph), it ispossible to lower the risk of such a mismatch with another person.

With the constitution of the third exemplary embodiment, the biologicalpattern information processing device 3, based information obtained bythe detection result obtaining unit 12, due to the repairing unit 214(of the modification thereof) performing repair of the biologicalpattern information, can perform a collation process using biologicalpattern information that has been repaired.

(Device User Interface)

Next, the device user interface according to each exemplary embodimentdescribed above (the first exemplary embodiment to third exemplaryembodiment, and modifications thereof) will be described.

FIG. 18 is a schematic diagram that shows a user interface whenobtaining a fingerprint image. The screen shown on the left side of FIG.18 is the display state prior to fingerprint acquisition. This screen(window) has the buttons “Obtain Fingerprint”, “Switch Display”,“Repair”, and “Collate”. When the “Obtain Fingerprint” button isdepressed by the user (specifically, when subjected to a click operationusing a mouse that is a pointing device), an external fingerprintobtaining means reads a fingerprint and the fingerprint obtaining unit11 reads that fingerprint image. As shown in the screen (window) on theright side of FIG. 18, the biological pattern information processingdevice (1, 2, 3) displays the read fingerprint in the region on the leftside of the window. The collating unit 116 collates this fingerprint anda pre-registered fingerprint. When there is a matching fingerprint, animage of the matched fingerprint and the identification information ofthe person having that fingerprint (individual ID or name) are displayedin the region on the right side of this window. In FIG. 18, a facialphotograph of the person corresponding to the matched fingerprint andthe matched finger type (“right hand index finger”) are also shown.

In the user interface described in FIG. 18, the portion relating to thecollation process is not included in the first exemplary embodiment.Also, the portion relating to the process of repairing a damaged portionof biological pattern information is not included in the first exemplaryembodiment and the second exemplary embodiment.

FIG. 19 is a schematic diagram that shows the user interface in the caseof a unique region being detected in the obtained fingerprint image.When the “Obtain Fingerprint” button has been depressed by the user inthe screen shown in the upper part of FIG. 19, the screen transitions tothe screen shown on the left side in the lower part of FIG. 19.

In FIG. 19, the arrow A1 indicates the display of a message when thereis a damage location. The arrow A2 indicates the display of afingerprint as is when there is no damage location. As described below,the screen of portion (a1) of FIG. 19 is the screen in the case ofdisplaying a fingerprint image and a damage location (however, whenthere is no damage location, a damage location is not displayed). Thescreen of portion (b1) of FIG. 19 is the screen in the case ofdisplaying only the damage location. The screen of portion (c1) of FIG.19 is the screen in the case of displaying only the fingerprint image.

In the left-side region of the screen shown in the lower part of FIG.19, a fingerprint image is shown. At this time, it is detected by theinformation obtained by the detection result obtaining unit 12 that thefingerprint image includes a unique region. In the screen on the leftside in the lower part of FIG. 19, the unique region in the fingerprintimage is displayed with a display attribute which is different from thatused for the other region. In the present case, specifically, thedisplay control unit (21, 121) performs control so as to display theunique region and the other region in different colors. That is, in thisscreen (the screen of unit (a1)), both the fingerprint image and thedamage location are displayed.

The unique region may also be displayed in a flashing manner. The colorof the unique region may be made different from that of the otherregion, and only the unique region may be displayed in a flashingmanner.

Since it has been established that a unique region (damage location of afingerprint) is included in this fingerprint image, the biologicalpattern information processing device displays a popup screen (arrowA1). Displayed in the popup screen is the message “There is a damagelocation in the fingerprint image. Re-obtain fingerprint at differentfinger?” In this situation, the user can choose between either “Yes (Y)”or “No (N)”.

The description will continue, returning to the screen on the left sideof the lower part of FIG. 19. When the “Switch Display” button in thescreen is depressed, the screen transitions to the screen in the middleof the lower part of FIG. 19 (the screen of the portion (b1)). In thescreen in the middle of the lower part of FIG. 19, only the damagelocation (unique region) is displayed, with the fingerprint image notbeing displayed.

When the “Switch Display” button is depressed in the middle screen ofthe lower part of FIG. 19, the screen transitions to the screen on theright side of the lower part of FIG. 19 (the screen of portion (c1)). Inthe screen on the right side of the lower part of FIG. 19, only thefingerprint image is displayed on the left side region, with informationindicating the damage location (unique region) not being displayed.

When the “Switch Display” button is depressed in the screen on the rightside of the lower part of FIG. 19, the screen transitions (returns) tothe screen on the left side of the lower part of FIG. 19.

That is, by means of the Switch Display button, it is possible tosequentially cycle the screen between “fingerprint image+damage location(unique region)”, “damage location (unique region) only”, and “onlyfingerprint image”.

That is, the display control unit controls the display so as to switchbetween a display of either one of the unique region and a region otherthan the unique region, and a display of both the unique region and aregion other than the unique region.

By performing control of such a switching display, the user can visuallydetermine whether there are damage marks by confirming only the uniqueregion.

FIG. 20 is a schematic diagram that shows the user interface that allowsa user to select the manner of the collation process when a uniqueregion is detected in the obtained fingerprint image.

In FIG. 20, the arrow A3 indicates the display of a message when thereis a damage location. As described below, the screen of unit (a2) ofFIG. 20 is the screen for type (1-1), that is, the case of no collationcondition. The screen of unit (b2) of FIG. 20 is the screen for type(1-2), that is, the case of no exclusion of a damage location. Thescreen of unit (c2) of FIG. 20 is the screen for type (1-3), that is,the case of the mismatch tolerance being relaxed.

The screen (window) on the left side of the upper part of FIG. 20 is thesame as the screen on the left side of the upper part of FIG. 19.

In the user interface shown in FIG. 20, when a damage location (uniqueregion) has been detected in the obtained fingerprint image, the usercan select a suitable operation from three types of operations. Thethree types are the following (1-1) to (1-3).

Type (1-1): Performs collation as is (no collation condition).

Type (1-2): Extracts only the portion estimated to not be damaged, andperforms collation with the information only of that portion (damagelocation exclusion).

Type (1-3): Performs collation by relaxing the misalignment toleranceand the mismatch tolerance of the fingerprint features during collation(tolerance relaxation).

The collating unit 116 performs collation processing with the conditionselected by the user among these.

When there is a damage location, and as a result of the collationprocess a fingerprint that matches is found, the background color of thematched information is changed for emphasis. In doing so, indication isgiven as to under which condition among the aforementioned threeconditions was the match found by the collation (for example, “Collationcondition: damage location exclusion” or “Collation condition: mismatchtolerance relaxation” and the like).

The user interface described in FIG. 20 is unrelated to the firstexemplary embodiment in which a collation process is not performed.

FIG. 21 is a schematic diagram that shows a user interface related tothe repair process of a damage location (unique region).

The fingerprint shown in the screen on the left side of the upper partof FIG. 21 includes a damage location (unique region). The user is ableto press the “Repair” button. In this situation, the message “Repair ofthe damage location will be performed. Please click the damagelocation.” is displayed in a popup screen. When the user presses the“OK” button, the process to repair the damage location is executed. Itis also possible to automatically perform repair of the damage locationon the basis of the ridge direction in the vicinity of the damagelocation as described above.

The screen on the left side of the bottom part of FIG. 21 is a displayexample following execution of the repair process. In this situation,when the user presses the “Collation” button, the collating unit 116performs the collation process using the fingerprint image after repair.

When a match is found among pre-registered fingerprints, as shown in thescreen on the right side of the lower part of FIG. 21, the matchedfingerprint image and the individual identification information aredisplayed. A facial photograph may also be displayed along with theindividual identification information.

That is, the display control unit performs control so as to obtain anddisplay biological pattern information that has been repaired tobiological pattern information with no unique region on the basis of theunique region information.

Thereby, the user can visually confirm the repaired image.

The user interface described in FIG. 21, being premised on a repairprocess, is unrelated to the first exemplary embodiment and secondexemplary embodiment.

The functions of the biological pattern information processing deviceaccording to the exemplary embodiments and modifications described abovemay be realized by a computer. In that case, a program for realizing thefunctions of this device may be recorded in a computer-readablerecording medium, with the program recorded on this recording mediumbeing read into a computer system and executed. Note that “computersystem” here includes an OS or hardware such as a peripheral. Further,“computer-readable recording medium” refers to a portable medium such asa flexible disk, a magneto-optical disk, a ROM, a CD-ROM or a storagedevice such as a hard disk built in the computer system. Furthermore,“computer-readable recording medium” may include a medium thatdynamically holds a program for a short period of time, such as acommunication line when a program is transmitted via a network such asthe Internet or a communication line such as a telephone line, and amedium that holds a program in a fixed period of time, such as avolatile memory in a computer system serving as a server or client inthe above situation. The aforementioned program may be one forimplementing some of the above functions, or the above functions may beimplemented in combination with a program already recorded on thecomputer system.

Each of the exemplary embodiments may be carried out as the followingmodification. That is, when biological pattern information obtained bythe biological pattern information obtaining unit is judged to include aunique region on the basis of information of a unique region (damagelocation) in biological pattern information obtained by the uniqueregion detection result obtaining unit, an authenticating unit performsan authentication process using information for authentication otherthan that biological pattern information. Specifically, when it becomesclear that a fingerprint that is biological pattern information includesa unique region, an authentication means other than a fingerprint image(authentication by facial recognition, authentication by vein patternrecognition, and the like) is used. The biological pattern informationprocessing device includes such an authenticating unit.

Exemplary embodiments of the present invention have been described indetail with reference to the drawings. However, specific configurationsare not limited to the described exemplary embodiments, and designs notdeparting from the scope of the invention are included.

This application is based upon and claims the benefit of priority fromJapanese patent application No. 2015-074424, filed Mar. 31, 2015, thedisclosure of which is incorporated herein in its entirety by reference.

INDUSTRIAL APPLICABILITY

The present invention can be utilized in a social system that usesfingerprint collation.

REFERENCE SYMBOLS

-   -   1, 2, 3: Biological pattern information processing device    -   11: Biological pattern information obtaining unit    -   12: Unique region detection result obtaining unit    -   21, 121: Display control unit    -   61: Unique region detecting unit    -   62: Pre-registered biological pattern information storage unit    -   91, 93: Damaged area detecting unit    -   92: Z-plasty operation fingerprint restoring unit    -   94: Damaged area removing unit    -   116: Collating unit    -   214, 214 a: Repairing unit

The invention claimed is:
 1. A fingerprint information processing devicecomprising: at least one memory storing instructions; and at least oneprocessor configured to execute the instructions to: obtain uniqueregion information that is detected based on fingerprint informationrepresenting a fingerprint, the unique region information representing aunique region included in the fingerprint; cause a display attribute,the unique region, and a region of the fingerprint other than the uniqueregion to be displayed based on the obtained unique region information,the display attribute being indicative of being the unique region;cause, according to a type of the unique region, a process that isexecutable with respect to the unique region to be displayed; determinewhether or not the unique region was produced by Z-plasty; and cause abutton for selecting whether or not to perform a repair process to bedisplayed when it is determined that the unique region was produced bythe Z-plasty.
 2. The fingerprint information processing device accordingto claim 1, wherein the at least one processor is configured to executethe instructions to: cause the type of the unique region to be displayedbased on the unique region information.
 3. The fingerprint informationprocessing device according to claim 1, wherein the at least oneprocessor is configured to execute the instructions to: switch displaybetween: display of the unique region; display of the region of thefingerprint other than the unique region; and both of the display of theunique region and the display of the region of the fingerprint otherthan the unique region.
 4. The fingerprint information processing deviceaccording to claim 1, wherein the at least one processor is configuredto execute the instructions to: obtain fingerprint information that hasbeen repaired to fingerprint information with no unique region based onthe unique region information; and cause the repaired fingerprintinformation to be displayed.
 5. The fingerprint information processingdevice according to claim 1, wherein the display attribute is anattribute that enables the unique region to be distinguished from theregion of the fingerprint other than the unique region.
 6. Thefingerprint information processing device according to claim 1, whereinthe at least one processor is configured to execute the instructions to:determine an abnormality degree of the unique region.
 7. The fingerprintinformation processing device according to claim 6, wherein theabnormality degree is determined based on at least one of directionchange of a ridge of the fingerprint or pitch change of the ridge. 8.The fingerprint information processing device according to claim 6,wherein the abnormality degree is expressed with gradations.
 9. Thefingerprint information processing device according to claim 1, whereinthe at least one processor is further configured to execute theinstructions to: cause a button to be displayed for selecting whether ornot to perform a collation process using the fingerprint information inwhich unique region has been repaired by the repair process.
 10. Afingerprint information processing method comprising: obtaining uniqueregion information that is detected based on fingerprint informationrepresenting a fingerprint, the unique region information representing aunique region included in the fingerprint; causing a display attribute,the unique region, and a region of the fingerprint other than the uniqueregion to be displayed based on the obtained unique region information,the display attribute being indicative of being the unique region;causing, according to a type of the unique region, a process that isexecutable with respect to the unique region to be displayed;determining whether or not the unique region was produced by Z-plasty;and causing a button for selecting whether or not to perform a repairprocess to be displayed when it is determined that the unique region wasproduced by the Z-plasty.
 11. The fingerprint information processingmethod according to claim 10, further comprising: causing the type ofthe unique region to be displayed based on the unique regioninformation.
 12. The fingerprint information processing method accordingto claim 10, further comprising: switching display between: display ofthe unique region; display of the region of the fingerprint other thanthe unique region; and both of the display of the unique region and thedisplay of the region of the fingerprint other than the unique region.13. The fingerprint information processing method according to claim 10,further comprising: obtaining fingerprint information that has beenrepaired to fingerprint information with no unique region based on theunique region information; and causing the repaired fingerprintinformation to be displayed.
 14. The fingerprint information processingmethod according to claim 10, wherein the display attribute is anattribute that enables the unique region to be distinguished from theregion of the fingerprint other than the unique region.
 15. Anon-transitory computer-readable recording medium storing a program thatcauses a computer to execute: obtaining unique region information thatis detected based on fingerprint information representing a fingerprint,the unique region information representing a unique region included inthe fingerprint; causing a display attribute, the unique region, and aregion of the fingerprint other than the unique region to be displayedbased on the obtained unique region information, the display attributebeing indicative of the unique region; causing, according to a type ofthe unique region, a process that is executable with respect to theunique region to be displayed; determining whether or not the uniqueregion was produced by Z-plasty; and causing a button for selectingwhether or not to perform a repair process to be displayed when it isdetermined that the unique region was produced by the Z-plasty.